title: A high-throughput framework to detect synapses in electron microscopy images.
abstract: BACKGROUND
  Synaptic connections underlie learning and memory in the brain and are dynamically formed and eliminated during development and in response to stimuli. Quantifying changes in overall density and strength of synapses is an important pre-requisite for studying connectivity and plasticity in these cases or in diseased conditions. Unfortunately, most techniques to detect such changes are either low-throughput (e.g. electrophysiology), prone to error and difficult to automate (e.g. standard electron microscopy) or too coarse (e.g. magnetic resonance imaging) to provide accurate and large-scale measurements.
  
  
  RESULTS
  To facilitate high-throughput analyses, we used a 50-year-old experimental technique to selectively stain for synapses in electron microscopy images, and we developed a machine-learning framework to automatically detect synapses in these images. To validate our method, we experimentally imaged brain tissue of the somatosensory cortex in six mice. We detected thousands of synapses in these images and demonstrate the accuracy of our approach using cross-validation with manually labeled data and by comparing against existing algorithms and against tools that process standard electron microscopy images. We also used a semi-supervised algorithm that leverages unlabeled data to overcome sample heterogeneity and improve performance. Our algorithms are highly efficient and scalable and are freely available for others to use.
  
  
  BACKGROUND
  Code is available at http://www.cs.cmu.edu/∼saketn/detect_synapses/
authors.affiliation: Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
authors.forename: Saket
authors.initials: S
authors.lastname: Navlakha
authors.forename: Joseph
authors.initials: J
authors.lastname: Suhan
authors.forename: Alison L
authors.initials: AL
authors.lastname: Barth
authors.forename: Ziv
authors.initials: Z
authors.lastname: Bar-Joseph
mesh_terms: D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D051379:Mice; D008854:Microscopy, Electron / Q000379:methods*; D013003:Somatosensory Cortex / Q000254:growth & development / Q000648:ultrastructure; D013569:Synapses / Q000648:ultrastructure*